Generating and using temporal metadata partitions

ABSTRACT

Concepts and technologies are disclosed herein for generating and using temporal metadata partitions. Metadata can be stored in temporal metadata partitions based upon a time range included in the metadata. Furthermore, metadata can be stored in multiple temporal metadata partitions to which the metadata is relevant. As such, metadata can be stored in manner that allows event data to be understood in the context of temporally accurate and/or relevant metadata. Functionality for executing queries of event data and providing results in view of metadata, as well as the merging of multiple temporal metadata partitions also are disclosed.

BACKGROUND

This application relates generally to data management. Morespecifically, the disclosure provided herein relates to generating andusing temporal metadata partitions.

Some communications networks collect and analyze event data from varioussources and/or for various purposes. The event data may relate tovarious network functions, elements, devices, and/or systems. Thus, theevent data can include, for example, network traffic, device or systemutilization information, usage statistics, packet inspectioninformation, or the like.

Some types of data may not include any indication of a context or frameof reference for the collected and/or associated data points. Forexample, router utilization data may indicate a number of ports in useat a time at which the data is collected or transmitted. Such data mayor may not be useful without knowing a capacity of the router, forexample. Thus, some networks may store data that defines capacities ofdevices and/or other information that, in conjunction with the eventdata, can be used to determine percentage utilization or otherstatistics or information.

Because modern communication networks have grown exponentially over thepast several years, the amount of data collected and analyzed, as wellas the frequency with which data may be updated, has increased.Furthermore, some network operators have sought to rapidly expandnetworks to increase and/or to improve performance. Thus, someinformation used to understand event data may be outdated and/orotherwise useless at any particular time.

Similarly, some network operators or other data analysis entities mayuse historical data to understand growth and/or use of a network. Forexample, router utilization over time may be considered to determinewhen a router is to be updated or for other purposes. Because the datadescribing the capacity of the router may be updated when the capacityof the router changes, historical event data may be misunderstood. Inparticular, the historical event data may be interpreted in view of thedata describing a current capacity of the router.

SUMMARY

The present disclosure is directed to generating and using temporalmetadata partitions. A server computer may execute a data managementapplication that is configured to analyze metadata received at theserver computer as part of a data stream generated by a data source. Themetadata may be generated by a same data source that generates eventdata, though this is not necessarily the case. The event data caninclude data points or data values and timestamps reflecting a time atwhich the event data is captured and/or transmitted. The metadata caninclude a time range that defines times between which a data valueassociated with the metadata applies. Thus, for example, metadatadescribing a router capacity may define a value corresponding to thecapacity and a time range over which the capacity applies. The timerange can be defined as being bound by a lower time limit and an uppertime limit, an open-ended time range that begins with a lower timelimit, and/or an open-ended time range that ends with an upper timelimit.

The data management application can analyze the incoming metadata toidentify the time range and to generate temporal metadata partitionsthat store the metadata associated with a particular time or ranges oftime included in the time range. According to various embodiments of theconcepts and technologies disclosed herein, the metadata can be saved tomultiple temporal metadata partitions that are encompassed or overlappedby the time range included in the metadata. Thus, for example, metadatadefining a time range from January-March may be included in temporalmetadata partitions for January, February, and March. It should beunderstood that this embodiment is illustrative, and should not beconstrued as being limiting in any way.

The data management application also can be configured to consider themetadata stored in the temporal metadata partitions at query time and/orat other times. When a query is received, the data managementapplication can determine a time associated with the query and/orexecute the query against event data and determine a time based upon oneor more event data query results. The data management application canidentify one or more temporal metadata partitions that apply to thedetermined time and interpret the event data in view of the metadata.Thus, event data associated with a particular time can be interpreted inview of metadata associated with that particular time. The datamanagement application also can be configured to merge temporal metadatapartitions to reduce storage space associated with the metadata. Thetemporal metadata partitions can be merged by merging values or timeranges and storing the merged temporal metadata partitions in the datastore.

According to one aspect of the concepts and technologies disclosedherein, a method is disclosed. The method can include obtaining metadataat a server computer executing a data management application. Themetadata can include a data value and a time range associated with thedata value. The method also can include analyzing, by the servercomputer, the time range to identify a temporal metadata partition inwhich the metadata is to be stored, and storing, by the server computer,the metadata in the temporal metadata partition.

In some embodiments, the method also can include determining, based uponthe time range, if the metadata is to be stored in a further temporalmetadata partition, and in response to a determination that the metadatais to be stored in the further temporal metadata partition, storing themetadata in the further temporal metadata partition. The metadata can beincluded in a data stream generated by a data source. In someembodiments, the data stream can include the metadata and event data,and the metadata can define a context of the event data. The method alsocan include receiving a query, executing the query against event datastored in a temporal data partition to obtain an event data queryresult, identifying, in the event data query result, a timestamp, andretrieving the metadata from a relevant temporal metadata partitionbased upon the timestamp. The method also can include computing resultsbased upon the metadata and the event data, and outputting the results.

In some embodiments, the metadata can provide a context of the eventdata and computing the results can include selecting event data based,at least partially, upon the metadata. The method also can includedetermining, based upon the time range, that the metadata is to bestored in a further temporal metadata partition, storing the metadata inthe further temporal metadata partition, determining that the temporalmetadata partition and the further temporal metadata partition are to bemerged, and merging the temporal metadata partition and the furthertemporal metadata partition. The method also can include determiningthat the temporal metadata partition and the further temporal metadatapartition are to be merged by selecting the temporal metadata partition,and identifying the further temporal metadata partition as a relatedtemporal metadata partition. The method also can include merging thetemporal metadata partition and the further temporal metadata partitionby merging a time range of the temporal metadata partition with afurther time range of the further temporal metadata partition togenerate a merged temporal metadata partition having a merged time rangeand a data value, and storing the merged temporal metadata partition.

According to another aspect of the concepts and technologies disclosedherein, a system is disclosed. The system can include a processor and amemory storing computer-executable instructions. When thecomputer-executable instructions are executed by the processor, theprocessor can perform operations including obtaining metadata includinga data value and a time range associated with the data value, analyzingthe time range to identify a temporal metadata partition in which themetadata is to be stored, determining, based upon the time range, thatthe metadata is to be stored in a further temporal metadata partition,storing the metadata in a further temporal metadata partition, andstoring the metadata in the temporal metadata partition.

In some embodiments, the computer-executable instructions, when executedby the processor, can cause the processor to perform operations that canfurther include receiving a query, executing the query against eventdata stored in a temporal data partition to obtain an event data queryresult, identifying, in the event data query result, a timestamp, andretrieving the metadata from a relevant temporal metadata partitionbased upon the timestamp. The computer-executable instructions, whenexecuted by the processor, can further cause the processor to performoperations that include computing results based upon the metadata andthe event data, and outputting the results. The computer-executableinstructions, when executed by the processor, can cause the processor toperform operations that include determining that the temporal metadatapartition and the further temporal metadata partition are to be merged,and merging the temporal metadata partition and the further temporalmetadata partition.

In some embodiments, the computer-executable instructions, when executedby the processor, can cause the processor to perform operations thatinclude determining that the temporal metadata partition and the furthertemporal metadata partition are to be merged by selecting the temporalmetadata partition, and identifying the further temporal metadatapartition as a related temporal metadata partition. Thecomputer-executable instructions, when executed by the processor, alsocan cause the processor to perform operations that include merging thetemporal metadata partition and the further temporal metadata partitionby merging a time range of the temporal metadata partition with afurther time range of the further temporal metadata partition togenerate a merged temporal metadata partition having a merged time rangeand a data value, and storing the merged temporal metadata partition.

According to yet another aspect, a computer storage medium is disclosed.The computer storage medium can have computer-executable instructionsstored thereon. The computer-executable instructions, when executed by aprocessor, can cause the processor to perform operations includingobtaining metadata including a data value and a time range associatedwith the data value, analyzing the time range to identify a temporalmetadata partition in which the metadata is to be stored, determining,based upon the time range, that the metadata is to be stored in afurther temporal metadata partition, storing the metadata in a furthertemporal metadata partition, and storing the metadata in the temporalmetadata partition.

In some embodiments, the computer-executable instructions, when executedby the processor, can cause the processor to perform operations furtherincluding receiving a query, executing the query against event datastored in a temporal data partition to obtain an event data queryresult, identifying, in the event data query result, a timestamp, andretrieving the metadata from a relevant temporal metadata partitionbased upon the timestamp. The computer-executable instructions, whenexecuted by the processor, can cause the processor to perform operationsfurther including determining that the temporal metadata partition andthe further temporal metadata partition are to be merged, and mergingthe temporal metadata partition and the further temporal metadatapartition.

In some embodiments, the computer-executable instructions, when executedby the processor, can cause the processor to perform operations furtherincluding determining that the temporal metadata partition and thefurther temporal metadata partition are to be merged by selecting thetemporal metadata partition, and identifying the further temporalmetadata partition as a related temporal metadata partition. Thecomputer-executable instructions, when executed by the processor, cancause the processor to perform operations further including merging thetemporal metadata partition and the further temporal metadata partitionby merging a time range of the temporal metadata partition with afurther time range of the further temporal metadata partition togenerate a merged temporal metadata partition having a merged time rangeand a data value, and storing the merged temporal metadata partition. Insome embodiments, the metadata can be included in a data streamgenerated by a data source, the data stream can include the metadata andevent data, the metadata can define a context of the event data, and thetemporal metadata partitions can be stored at a distributed database.

Other systems, methods, and/or computer program products according toembodiments will be or become apparent to one with skill in the art uponreview of the following drawings and detailed description. It isintended that all such additional systems, methods, and/or computerprogram products be included within this description, be within thescope of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system diagram illustrating an illustrative operatingenvironment for the various embodiments disclosed herein.

FIG. 2 is a flow diagram showing aspects of a method for storingmetadata in multiple temporal metadata partitions, according to anillustrative embodiment.

FIG. 3 is a flow diagram showing aspects of a method for executing aquery against event data using metadata stored in temporal metadatapartitions, according to another illustrative embodiment.

FIG. 4 is a flow diagram showing aspects of a method for mergingtemporal metadata partitions, according to another illustrativeembodiment.

FIG. 5 schematically illustrates a network, according to an illustrativeembodiment.

FIG. 6 is a block diagram illustrating an example computer systemconfigured to generate and use temporal data partition revisions,according to some illustrative embodiments.

DETAILED DESCRIPTION

The following detailed description is directed to generating and usingtemporal metadata partitions. A server computer can execute a datamanagement application. The data management application can beconfigured to analyze metadata received at the server computer as partof a data stream generated by a data source. The data stream also caninclude event data that can include data points and timestampsreflecting one or more times at which the event data is captured and/ortransmitted. The metadata can include a time range that defines timesbetween which a data value included in the metadata applies. The timerange can be defined as being bound by a lower time limit and an uppertime limit. The time range also can be defined as an open-ended timerange having only a lower time limit or only an upper time limit.

The data management application can analyze the metadata to identify atime range associated with the metadata. The data management applicationcan store the metadata in one or more temporal metadata partitionscorresponding to a particular time, times, or time ranges included inthe time range of the metadata. The metadata can be stored in multipletemporal metadata partitions that overlap the time range included in themetadata. The data management application also can be configured tomerge temporal metadata partitions to reduce storage space associatedwith the metadata. The temporal metadata partitions can be merged bymerging values or time ranges and storing the merged temporal metadatapartitions in the data store.

The data management application also can use the metadata stored in thetemporal metadata partitions at query time and/or at other times. When aquery is received, the data management application can determine a timeassociated with the query and/or execute the query against event dataand determine a time based upon one or more event data query results.The data management application can identify one or more temporalmetadata partitions that apply to the determined time and interpret theevent data in view of the metadata. As such, embodiments of the conceptsand technologies disclosed herein can be used to allow event data to beinterpreted and/or analyzed in view of temporally appropriate and/orotherwise relevant metadata.

While the subject matter described herein is presented in the generalcontext of program modules that execute in conjunction with theexecution of an operating system and application programs on a computersystem, those skilled in the art will recognize that otherimplementations may be performed in combination with other types ofprogram modules. Generally, program modules include routines, programs,components, data structures, and other types of structures that performparticular tasks or implement particular abstract data types. Moreover,those skilled in the art will appreciate that the subject matterdescribed herein may be practiced with other computer systemconfigurations, including hand-held devices, multiprocessor systems,microprocessor-based or programmable consumer electronics,minicomputers, mainframe computers, and the like.

Referring now to FIG. 1, aspects of an operating environment 100 forvarious embodiments of the concepts and technologies disclosed hereinfor generating and using temporal metadata partitions will be described,according to an illustrative embodiment. The operating environment 100shown in FIG. 1 includes a computing device such as a server computer(“server computer”) 102. While referred to herein as a “servercomputer,” it should be understood that in various embodiments of theconcepts and technologies disclosed herein the functionality of theserver computer 102 can be provided by other computing systems such as,for example, desktop computers, laptop computers, other computingsystems, combinations thereof, or the like. Thus, the exampleembodiments of the server computer 102 described herein as a web serveror other server computer are illustrative and should not be construed asbeing limiting in any way.

The server computer 102 can be configured to operate in communicationwith and/or as part of a communications network (“network”) 104. Thus,communications described herein as occurring with or via the servercomputer 102 should be understood as being capable of occurring via thenetwork 104. The server computer 102 can execute an operating system 106and one or more application programs such as, for example, a datamanagement application 108 and/or other application programs (notillustrated). The operating system 106 can include a computer programfor controlling the operation of the server computer 102. The datamanagement application 108 can include an executable program configuredto execute on top of the operating system 106 to provide thefunctionality described herein for generating and using temporal datapartitions.

The data management application 108 can be configured to obtain andmanage storage of data associated with one or more streams of data(“data streams”) 110. The data streams 110 can be received or otherwiseobtained from one or more data sources 112A-N (hereinafter collectivelyand/or generically referred to as “data sources 112”). As shown in FIG.1, the data streams 110 can include event data 114 and metadata 116. Theevent data 114 and the metadata 116 are described in more detail below.

According to various embodiments, the data sources 112 can correspond toone or more real or virtual data storage devices, server computers,network reporting devices or systems, network analytics devices, trafficmonitors, deep packet inspection (“DPI”) devices or systems,combinations thereof, or the like. As such, the event data 114 includedin the data streams 110 can correspond to various types of streamingdata including, but not limited to, network statistics, stored data,media streams, packet inspection information, user information, trafficinformation, device output information, analytics, performancestatistics, device utilization and/or availability information,combinations thereof, or the like.

The metadata 116 included in the data streams 110 can be used to providecontext for the event data 114. Thus, for example, if the event data 114corresponds to a router utilization such as a number of occupied ports,the metadata 116 can correspond to an indication of a number ofavailable ports associated with the router. Thus, a percent utilizationof the router can be computed, in some embodiments, by analyzing theevent data 114 in light of the metadata 116. This and other aspects ofusing the metadata 116 are described in additional detail below. Becausethe data sources 112, their respective data streams 110, the event data114, and/or the metadata 116 can include almost any type of sourcesand/or types of data, it should be understood that the above examplesare illustrative and should not be construed as being limiting in anyway.

As shown in FIG. 1, the event data 114 included in the data streams 110can include data points and timestamps. Similarly, the metadata 116included in the data streams 110 can include one or more records 118. Asingle record 118 is shown in FIG. 1 to simplify illustration anddescription of the concepts and technologies disclosed herein, and notto limit the disclosure in any way. In light of the above, it should beunderstood that the illustrated record 118 can include multiple records118. As such, the description herein refers to multiple records 118and/or references a single record 118 as a generic representationthereof.

One or more records 118 can include a data value or other data point(“data value”) and a time range with which the data value is associated.According to various embodiments, though not illustrated in FIG. 1, thetime range of the records 118 can be defined by a lower time limit t_(l)and an upper time limit t_(h), though this is not necessarily the case.As such, the time range of the records 118 can be denoted as (t_(l),t_(h)). In some instances, the time ranges may include and/or may bedenoted as having a only lower time limit t_(l) or only an upper timelimit t_(h). Thus, a time range of the records 118 can indicate that aparticular value of the records 118 applies at any time after aparticular lower time limit t_(l) for records 118 having only a lowertime limit t_(l). Similarly, a time range can indicate a particularvalue as applying at any time before a particular upper time limit t_(h)for records 118 having only an upper time limit t_(h). Thus, time rangescan also be denoted as (t_(i), −) and/or (−, t_(h)) in addition to, orinstead of, (t_(i), t_(h)). It should be understood that theseembodiments are illustrative, and should not be construed as beinglimiting in any way.

The data value of the record 118 can include an integer value; a string;a Boolean value such as 0/1, true/false, yes/no, or the like; afunction; combinations thereof; or the like. As such, the record 118can, by including the data value and the time range, represent a datavalue that applies over a particular temporal limitation such as thetime range. As mentioned above, the metadata 116 can be used by theserver computer 102 to provide context for the event data 114. Thus, thetime range and the data value can be used by the server computer 102 tointerpret event data 114, as will be explained in more detail below.

The data management application 108 can be configured to obtain theevent data 114, the metadata 116, and/or other data associated with thedata streams 110. The server computer 102 also can be configured tostore the event data 114 or the metadata 116, or to generateinstructions for other devices or software to store the event data 114and/or the metadata 116 in a data storage device such as, for example,the data store 120. According to various embodiments of the concepts andtechnologies disclosed herein, the functionality of the data store 120can be provided by one or more databases, server computers, hard diskdrives, memory devices, desktop computers, laptop computers, othercomputing devices, other data storage devices, combinations thereof, orthe like. It should be understood that the data store 120 also caninclude or can be provided by a real or virtual data storage deviceand/or a collection of multiple data storage devices. For purposes ofillustrating the concepts and technologies disclosed herein, thefunctionality of the data store 120 is described herein as beingprovided by a server computer hosting a database. In view of theabove-described contemplated embodiments, it should be understood thatthis example of the data store 120 is illustrative, and should not beconstrued as being limiting in any way.

As shown in FIG. 1, the data management application 108 can beconfigured to obtain the event data 114 and the metadata 116, though notnecessarily at the same time, and to store these and/or other data astables, records, and/or other types of data or data structures. In theillustrated embodiment, the data management application 108 can beconfigured to store the event data 114 in one or more temporal datapartitions 122A-N (hereinafter collectively and/or generically referredto as “temporal data partitions 122”). Thus, the temporal datapartitions 122 can include one or more instances of data extracted fromor included in the event data 114 that can include a data point and atimestamp. Because the event data 114 can be stored in additional and/oralternative formats, it should be understood that this embodiment isillustrative, and should not be construed as being limiting in any way.

The data management application 108 also can be configured to store themetadata 116 in one or more temporal metadata partitions 124A-N(hereinafter collectively and/or generically referred to as “temporalmetadata partitions 124”). Although not visible in FIG. 1, the metadata116 stored in the temporal metadata partitions 124 can include one ormore records such as, for example, the record 118. Thus, the metadata116 stored in the temporal metadata partitions 124 can include datahaving data values and time ranges. The storage of the metadata 116 inthe temporal metadata partitions 124 is described in additional detailbelow, particularly with reference to FIG. 2.

The data management application 108 also can be configured tocommunicate with one or more computing devices such as, for example, theuser device 126 shown in FIG. 1 to satisfy one or more request.According to various embodiments, for example, the user device 126 cangenerate one or more queries 128 relating to the event data 114. As willbe explained in more detail herein, the data management application 108can be configured to receive the queries 128 and to execute the queries128 against the event data 114. The data management application 108 alsocan be configured to consider the metadata 116 when executing thequeries 128 against the event data 114. The metadata 116 can beconsidered by the data management application 108 to impart meaning toone or more results 130 obtained by the data management application 108during execution of the queries 128.

In particular, as explained above, the event data 114 may correspond,for example, to raw measurements or other types of data that may lackcontext for interpretations. Thus, for example, if the event data 114corresponds to router utilization statistics such as a number ofoccupied ports, the event data 114 may provide a raw number such aseighty, two thousand, or the like. The event data 114 may not, however,provide context for that information such as, for example, a totalnumber of available ports at the router. Thus, the data managementapplication 108 may be unable to interpret the event data 114 withoutsome metadata 116, which can be used to represent, for example, thetotal number of available ports at the router.

Another complication may be experienced with regard to the lack ofcontext. In particular, metadata such as the metadata 116 describedherein may be stored as a table or other data structure and may be usedto interpret the event data 114. The metadata 116, however, may not bestored in a temporal partition that can represent changes to themetadata 116 over time. Thus, for example, if the router at issue in theabove example had a total capacity of one thousand ports, the metadata116 may represent this capacity. If, however, the router is updated atsome time from having a capacity of one thousand ports to having acapacity of two thousand ports, the metadata 116 may be updated as well.Thus, if a user queries the event data 114 for router capacityinformation at some time prior to the updating of the router, themetadata 116 indicating a capacity of two thousand ports may be used tointerpret the event data 114, although the update may not yet haveoccurred when the considered event data 114 was captured.

To address this and other considerations, embodiments of the conceptsand technologies disclosed herein support storage of the metadata 116 intemporal metadata partitions 124. The temporal metadata partitions 124can be relevant to particular times and/or time ranges, and metadata 116can be stored in the temporal metadata partitions 124 based upon timeranges included in records 118 of the metadata 116. Thus, for example,the metadata 116 can be stored in a number of temporal metadatapartitions 124 to which the metadata 116 is relevant. In the illustratedembodiment of FIG. 1, a first temporal metadata partition 124A can storethe metadata 116 as being relevant to a first time or time range, and annth temporal metadata partition 124N can store the same metadata 116 asbeing relevant to an nth time or time range. Thus, metadata 116 can bestored to any number of temporal metadata partitions 124 that includetimes or time ranges to which the metadata 116 applies.

In an embodiment of the data management application 108, metadata 116 isobtained at the server computer 102 and analyzed by the data managementapplication 108 to identify a time range of the metadata 116. The datamanagement application 108 identifies a temporal metadata partition 124to which the time range of the metadata 116 corresponds and copies themetadata 116 to the identified temporal metadata partition 124. The datamanagement application 108 can repeat these operations to store themetadata 116 into a number of temporal metadata partitions 124 thatoverlap the time range of the metadata 116. Thus, for example, if thetemporal metadata partitions 124 are divided into time ranges coveringone month, and if the metadata 116 includes a time range of one year,the metadata 116 can be copied into twelve temporal metadata partitions124, one for each month. Because other time ranges and/or timeincrements of the metadata 116 and/or the temporal metadata partitions124 are possible and are contemplated, it should be understood that thisembodiment is illustrative, and should not be construed as beinglimiting in any way.

Embodiments of the concepts and technologies disclosed herein alsosupport merging of temporal metadata partitions 124 to save or createstorage space at the data store 120. The data management application 108can be configured to select a temporal metadata partition 124 and toidentify one or more related temporal metadata partitions 124. It can beappreciated that multiple temporal metadata partitions 124 may berelated based upon time ranges, data values, and/or other aspects of themetadata 116 stored by the temporal metadata partitions 124. Thus, thedata management application 108 can identify related temporal metadatapartitions 124 and merge the temporal metadata partitions 124.

If the temporal metadata partitions 124 contain metadata 116 havingsimilar or identical data values but disparate time ranges, the temporalmetadata partitions 124 can be merged to reflect the same data value(s)and a combined time range that includes or encompasses multiple timeranges associated with the multiple temporal metadata partitions 124.Additionally, or alternatively, if the time ranges of the temporalmetadata partitions 124 are the same or similar, but the data values aredisparate, the data management application 108 can be configured tomerge the temporal metadata partitions 124 by combining the data values(if applicable) and reflecting the same time range(s). Additionaldetails of merging temporal metadata partitions 124 are set forth belowwith reference to FIG. 4.

FIG. 1 illustrates one server computer 102, one network 104, two datasources 112, one data store 120, and one user device 126. It should beunderstood, however, that various implementations of the operatingenvironment 100 include multiple server computers 102; multiple networks104; less than two, two, and/or more than two data sources 112; multipledata stores 120; and/or multiple user devices 126. As such, theillustrated embodiment should be understood as being illustrative, andshould not be construed as being limiting in any way.

Turning now to FIG. 2, aspects of a method 200 for storing metadata inmultiple temporal metadata partitions will be described in detail,according to an illustrative embodiment. It should be understood thatthe operations of the methods disclosed herein are not necessarilypresented in any particular order and that performance of some or all ofthe operations in an alternative order(s) is possible and iscontemplated. The operations have been presented in the demonstratedorder for ease of description and illustration. Operations may be added,omitted, and/or performed simultaneously, without departing from thescope of the concepts and technologies disclosed herein.

It also should be understood that the methods disclosed herein can beended at any time and need not be performed in its entirety. Some or alloperations of the methods, and/or substantially equivalent operations,can be performed by execution of computer-readable instructions includedon a computer storage media, as defined herein. The term“computer-readable instructions,” and variants thereof, as used herein,is used expansively to include routines, applications, applicationmodules, program modules, programs, components, data structures,algorithms, and the like. Computer-readable instructions can beimplemented on various system configurations including single-processoror multiprocessor systems, minicomputers, mainframe computers, personalcomputers, hand-held computing devices, microprocessor-based,programmable consumer electronics, combinations thereof, and the like.

Thus, it should be appreciated that the logical operations describedherein are implemented (1) as a sequence of computer implemented acts orprogram modules running on a computing system and/or (2) asinterconnected machine logic circuits or circuit modules within thecomputing system. The implementation is a matter of choice dependent onthe performance and other requirements of the computing system.Accordingly, the logical operations described herein are referred tovariously as states, operations, structural devices, acts, or modules.These states, operations, structural devices, acts, and modules may beimplemented in software, in firmware, in special purpose digital logic,and any combination thereof. As used herein, the phrase “cause aprocessor to perform operations” and variants thereof is used to referto causing a processor of a computing system or device, such as, forexample, the server computer 102 to perform one or more operationsand/or causing the processor to direct other components of the computingsystem or device to perform one or more of the operations.

For purposes of illustrating and describing the concepts of the presentdisclosure, the methods disclosed herein are described as beingperformed by the server computer 102 via execution of one or moresoftware modules such as, for example, the data management application108. It should be understood that additional and/or alternative devicesand/or network nodes can provide the functionality described herein viaexecution of one or more modules, applications, and/or other softwareincluding, but not limited to, the data management application 108.Thus, the illustrated embodiments are illustrative, and should not beviewed as being limiting in any way.

The method 200 begins at operation 202, wherein the server computer 102obtains metadata 116. According to various implementations of theconcepts and technologies disclosed herein, the server computer 102 canobtain the metadata 116 as, or as a part of, a data stream 110 that canbe received, retrieved, and/or otherwise obtained by the server computer102. According to various embodiments, the data sources 112 can beconfigured to stream the metadata 116 in or as the data streams 110 tothe server computer 102. The metadata 116 may be reported at oraccording to almost any time, frequency, or schedule such as, forexample, once a second, once a minute, once an hour, once a day, once aweek, once a month, other times, combinations thereof, or the like. Theevent data 114 may be streamed to the server computer 102 at oraccording to the same and/or different frequencies, intervals, times,and/or schedules.

In one contemplated embodiment, the metadata 116 is streamed to theserver computer 102 as a daily report on changes made to the network 104and/or a portion thereof. In some other embodiments, the metadata 116 isstreamed to the server as temporal releases of metadata 116 by the datasources 112 at five minutes intervals, hourly, daily, weekly, monthly,combinations thereof, or the like. Thus, the metadata 116 obtained inoperation 202 can correspond to a temporal release of the metadata 116in one or more of the data streams 110, though this is not necessarilythe case.

As illustrated in FIG. 1, the metadata 116 obtained in operation 202 caninclude a record 118 that has a data value and a time range. Becausemultiple records 118 can be received or otherwise obtained by the servercomputer 102 at operation 202, it should be understood that the exampleof one record 118 as shown in FIG. 1 is merely illustrative and isprovided to simplify description of the concepts and technologiesdisclosed herein. Thus, this example is illustrative, and should not beconstrued as being limiting in any way.

From operation 202, the method 200 proceeds to operation 204, whereinthe server computer 102 analyzes the time range included in the record118 of the metadata 116. The time range can define at least one of alower time limit t_(l) and an upper time limit t_(h). In someembodiments, a particular data value included in the record 118 mayapply from the lower time limit t_(l) until a present time, and as suchan upper time limit t_(h) may not be included in the record 118. In thedescribed embodiment of the method 200, the record 118 is described asincluding the lower time limit t_(l) and the upper time limit t_(h).Thus, the server computer 102 can analyze, in operation 204, the timerange defined by these two limits to define the range over which thedata value included in the record 118 applies.

By way of example, the record 118 may include a data value of forty.Similarly, the record 118 may include a lower time limit t_(l) thatspecifies a time of Jan. 28, 2017 08:17:24 AM and an upper time limitt_(h) that specifies a time of Jan. 28, 2018 11:52:17 AM. In thisexample, the server computer 102 can be configured to analyze the record118 to define a range between these two times as the time range overwhich the data value forty applies. Because the record 118 can includealmost any data value in almost any format and over almost any timerange, it should be understood that this embodiment is illustrative, andshould not be construed as being limiting in any way.

From operation 204, the method 200 proceeds to operation 206, whereinthe server computer 102 identifies a temporal metadata partition 124 towhich the metadata 116 obtained in operation 202 is to be stored. Theserver computer 102 can be configured to analyze the time range analyzedin operation 204, as well as time ranges and/or time values of thetemporal metadata partitions 124 stored at the data store 120. In someembodiments, as explained above, the server computer 102 can beconfigured to include a time range or time value in a name of thetemporal metadata partitions 124. As such, the server computer 102 canbe configured to analyze names of the temporal metadata partitions 124in operation 206 to identify the temporal metadata partition 124 towhich the metadata 116 is to be copied based upon the time rangeincluded in the metadata 116.

Thus, for example, if the metadata 116 includes the time range set forthin the example described with respect to operation 204 above, the servercomputer 102 can determine that a temporal metadata partition 124including values having timestamps including a date in May, 2017, and/orhaving a name or title indicating such a time indication, is a temporalmetadata partition 124 to which the metadata 116 is to be copied. Itshould be understood that this embodiment is illustrative, and shouldnot be construed as being limiting in any way.

From operation 206, the method proceeds to operation 208, wherein theserver computer 102 stores the metadata 116 obtained in operation 202 tothe temporal metadata partition 124 identified in operation 206. Thus,the temporal metadata partition 124 identified in operation 206 caninclude the record 118 included in the metadata 116 received inoperation 202.

From operation 208, the method 200 proceeds to operation 210, whereinthe server computer 102 can determine if the metadata 116 is to bestored in another temporal metadata partition 124. Thus, the servercomputer 102 can be configured to examine the names and/or contents ofthe temporal metadata partitions 124 to identify another temporalmetadata partition 124 to which the metadata 116 is to be copied. Thus,in the above example of the metadata 116 that includes a time range fromJan. 28, 2017 through Jan. 28, 2018, the server computer 102 canidentify one or more temporal metadata partitions 124 that include timeranges or points within that time range. Thus, for example, a temporalmetadata partition 124 that includes data for February of 2017 can beidentified, as can temporal metadata partitions 124 that include datafor March, 2017, April, 2017, May, 2017, or the like.

If the server computer 102 determines, in operation 210, that themetadata 116 is to be copied to another temporal metadata partition 124,the method 200 can return to operation 206, wherein the server computer102 can identify another temporal metadata partition 124. Thus, it canbe appreciated that operations 206-210 can be repeated by the servercomputer 102 until the metadata 116 has been copied to each of thetemporal metadata partitions 124 that include time-based data within thetime range included in the metadata 116.

It can be appreciated from the above description of operations 202-210that, a record 118 associated with the metadata 116 can be copied tomultiple temporal data partitions 124 by the server computer 102. Assuch, when a temporal metadata partition 124 is retrieved for executionof a query 128 against the event data 114 stored in the temporal datapartitions 122 described herein, the record 118 can be included in thetemporal metadata partition 124. An example method for executing a query128 using temporal metadata partitions 124 is set forth in additionaldetail below with reference to FIG. 3.

From operation 210, the method 200 proceeds to operation 212. The method200 ends at operation 212.

Turning now to FIG. 3, aspects of a method 300 for executing a queryagainst event data using metadata stored in temporal metadata partitionswill be described in detail, according to an illustrative embodiment.The method 300 begins at operation 302, wherein the server computer 102receives a query 128. The query 128 received in operation 202 caninclude a query 128 received from a requestor such as, for example, anetwork data analysis system, network operations personnel, and/or aconsumer or user of the event data 114 such as the user device 126. Insome embodiments, the query 128 can correspond to a standing queryexecuted periodically by the server computer 102 and/or one or morereporting devices in communication with the server computer 102.

In some embodiments, the query 128 received in operation 302 cancorrespond to a query 128 that is to be executed against the event data114 stored in the temporal data partitions 122 at the data store 120.Thus, for example, the event data 114 can correspond to routerutilization data and the query 128 can correspond to a request for dataabout router utilization percentage calculation. Because the query 128can be executed against other types of event data 114, it should beunderstood that this embodiment is illustrative, and should not beconstrued as being limiting in any way.

From operation 302, the method 300 proceeds to operation 304, whereinthe server computer 102 executes the query 128 against the event data114. Thus, the server computer 102 can, by executing the query 128against the event data 114, identify one or more records or other datapoints included in the event data 114 that correspond to or areresponsive to the query 128 received in operation 302. It should beunderstood that the server computer 102 can be configured to call aquery device or application and/or that the server computer 102 canexecute one or more query applications for executing the query 128. Assuch, operation 304 can include, in some embodiments, invokingfunctionality associated with a query application via a program calland/or via invoking a query application via an application programminginterface exposed by a query application or query device. By executingthe query 128 against the event data 114, the server computer 102 canidentify an event data query result.

From operation 304, the method 300 proceeds to operation 306, whereinthe server computer 102 identifies a timestamp of an event data queryresult. Because the event data 114 stored in the temporal datapartitions 122 can include timestamps, the server computer 102 can beconfigured to identify a timestamp of the event data 114 included in theevent data query result in operation 306. Because the server computer102 can identify multiple event data query results in operation 304, itshould be understood that the server computer 102 can repeat operation306 to identify a timestamp associated with one or more event data queryresults, though this is not the case. As such, the example of atimestamp as described herein should be understood as being illustrativeand should not be construed as being limiting in any way.

From operation 306, the method 300 proceeds to operation 308, whereinthe server computer 102 retrieves relevant metadata 116 from thetemporal metadata partitions 124. According to various embodiments, theserver computer 102 can identify “relevant” metadata 116 by identifyinga timestamp or time range associated with an event data query resultand/or the query 128. Thus, for example, if the query 128 requestsrouter data associated with a particular time such as, for example, themonth of February 2017, the server computer 102 can identify temporalmetadata partitions 124 that include metadata 116 having time rangesthat encompass or overlap February 2017. Because the server computer canidentify temporal metadata partitions 124 in additional or alternativeways, it should be understood that this embodiment is illustrative, andshould not be construed as being limiting in any way.

From operation 308, the method 300 proceeds to operation 310, whereinthe server computer 102 applies the metadata 116 retrieved in operation308 to the event data result obtained in operation 304. As explainedherein, the metadata 116 can provide context for the event data 114and/or an event data result based thereon. For example, if a query 128relates to a particular user's data plan and/or usage in a particularmonth, the server computer 102 can query event data 114 that includesdata usage of the user in that month. The metadata 116 can provide, forexample, an indication of what the user's plan was (e.g., ten GB permonth, twenty GB per month, or the like) at the time the event data 114was recorded.

To illustrate the usefulness of temporally partitioned metadata 116,metadata 116 stored in a first temporal metadata partition 124 mayindicate a plan of ten GB per month from January-July of 2017. Metadata116 stored in a second temporal metadata partition 124 may indicate aplan of twenty GB per month from August-September of 2017. Thus, if theevent data 114 indicates a consumption of fifteen GB, the metadata 116can be used to collectively indicate (with the event data 114) that theuser used 150% or 75% of his or her plan, depending upon which metadata116 is relevant to the event data 114. If the timestamp of the eventdata 114 indicates, for example, August, 2017, the server computer 102can interpret the event data 114 in view of the metadata 116 stored inthe second temporal metadata partition. Thus, it can be understood thatthe storage of metadata 116 in temporal metadata partitions 124 asdisclosed herein can be used to understand and/or impart meaning toevent data 114. It should be understood that the above example isillustrative and should not be construed as being limiting in any way.

As explained above, the server computer 102 can identify multipleresults in the query of the event data 114 in operation 304. As such,the server computer 102 can iterate operation 310 for each of the eventdata query results. Thus, the server computer 102 can be configured toapply relevant metadata 116 to each of the event data query results, insome embodiments.

From operation 312, the method 300 proceeds to operation 314, whereinthe server computer 102 outputs results 130. The results 130 output bythe server computer 102 in operation 314 can correspond to the eventdata 114 as interpreted in view of the applied metadata 116 from therelevant temporal metadata partitions 124. As such, embodiments of theconcepts and technologies disclosed herein can be used to respond toqueries 128 using metadata 116 stored in temporal metadata partitions124.

From operation 312, the method 300 proceeds to operation 314. The method300 ends at operation 314.

Turning now to FIG. 4, aspects of a method 400 for merging temporalmetadata partitions will be described in detail, according to anillustrative embodiment. The method 400 begins at operation 402, whereinthe server computer 102 can select a temporal metadata partition 124. Insome embodiments, the selection of the temporal metadata partition 124can correspond to the server computer 102 selecting a temporal metadatapartition 124 that is to be merged with another temporal metadatapartition 124.

The server computer 102 can determine that temporal metadata partitions124 are to be merged based upon a command or other trigger event. Forexample, the server computer 102 can be configured to merge temporalmetadata partitions 124 in response to receiving a command to mergetemporal metadata partitions 124, detecting storage of a certain numberof records 118 in the temporal metadata partitions 124, detectingexpiration of a timer that can be initiated with each temporal metadatapartition 124 merge operation, passage of a particular amount of timesince a last merge process, execution of a number of queries 128 orother actions, storage of a particular number of temporal metadatapartitions 124, combinations thereof, or the like.

It should be understood that a number of temporal metadata partitions124 or operations, an amount of time, and/or other amounts or number ofevents or items that may trigger a merge operation for temporal metadatapartitions 124 can be defined in various ways. For example, these andother trigger conditions may be defined by system or user settings,options, or the like. Because merging of temporal metadata partitions124 can be initiated for additional and/or alternative reasons, itshould be understood that the above examples are illustrative, andshould not be construed as being limiting in any way. Upon detecting atrigger to merge the temporal metadata partitions 124, the servercomputer 102 can select a temporal metadata partition 124.

From operation 402, the method 400 proceeds to operation 404, whereinthe server computer 102 identifies temporal metadata partitions 124related to the temporal metadata partition selected in operation 402.The server computer 102 can determine that a temporal metadata partition124 is related to another temporal metadata partition 124, for example,by determining that a particular record 118 is stored in both temporalmetadata partitions 124, by determining that a time range included inthe records 118 of multiple temporal metadata partitions 124 overlap,based upon keys, identifiers, and/or other data included in the temporalmetadata partitions 124, combinations thereof, or the like. Because theserver computer 102 can identify related temporal metadata partitions inadditional and/or alternative ways, it should be understood that theseembodiments are illustrative, and should not be construed as beinglimiting in any way. The server computer 102 can be configured to repeatoperation 404 until the server computer 102 determines that noadditional related temporal metadata partitions 124 exist. Thus, theserver computer 102 can identify, by repeating operation 404, allrelated temporal metadata partitions 124 stored at the data store 120.

From operation 404, the method 400 proceeds to operation 406, whereinthe server computer 102 can merge the related temporal metadatapartitions 124 identified in operations 402-404. In operation 406, theserver computer 102 can merge the temporal metadata partitions 124 bymerging data values of records 118 having a similar or identical timerange, by merging time ranges of records 118 having a similar oridentical data value, and/or by taking other actions to merge records118 of the temporal metadata partitions 124.

In some embodiments, the time ranges of the related temporal metadatapartitions 124 can be merged to reflect time ranges of the multipletemporal metadata partitions 124. Thus, for example, if time ranges oftemporal metadata partitions 124 are represented as (t_(l), t_(h)), timeranges of temporal metadata partitions 124 can be represented,respectively, as (t_(l1), t_(h1)) and (t_(l2), t_(h2)). Thus, in a mergeoperation, the server computer 102 can be configured to determine anearlier or later time among t_(l1), t_(l2) and an earlier or later timeamong t_(h1), t_(h2). In one contemplated embodiment, the servercomputer 102 selects a lowest time among the lower time limits t_(l1),t_(l2) and a highest time among the upper time limits t_(h1), t_(h2) andmodifies the time range of the temporal metadata partition 124 toreflect a time range with these selected time limits. Thus, the exampletemporal metadata partitions 124 above can be merged to obtain newtemporal metadata partition 124 having a time range (t_(l1), t_(h2)).Because the temporal metadata partitions 124 can be merged in additionaland/or alternative ways, it should be understood that this embodiment isillustrative, and should not be construed as being limiting in any way.

Similarly, the server computer 102 can be configured to merge temporalmetadata partitions 124 by merging data values of the temporal metadatapartitions 124 and maintaining the time ranges of the temporal metadatapartitions 124. Thus, for example, if time ranges of two or moretemporal metadata partitions 124 are represented as (t_(l1), t_(h1)),the server computer 102 can be configured to merge the values of thetemporal metadata partitions 124 and create a merged temporal metadatapartition 124 having a time range (t_(l1)t_(h1)). The data values of thetemporal metadata partitions 124 can be merged in any number of waysincluding, but not limited to, averaging the data values, summing thedata values, otherwise modifying the data values, combinations thereof,or the like. In some embodiments, the temporal metadata partitions 124can contain records r₁ and r₂. These records r₁, r₂ can have ranges(tl₁,th₁) and (tl₂, th₂), respectively. Furthermore, these records r₁,r₂ can be otherwise identical. In such a case, the records r₁, r₂ can bemerged into a single temporal metadata partition 124. Because thetemporal metadata partitions 124 can be merged in additional and/oralternative ways, it should be understood that these examples of mergingdata values are illustrative, and should not be construed as beinglimiting in any way.

From operation 406, the method 400 proceeds to operation 408, whereinthe server computer 102 saves the temporal metadata partition 124. Inparticular, the server computer 102 can save the temporal metadatapartition 124 generated by merging the temporal metadata partitions 124in operation 406 in the data store 120. Because the temporal metadatapartition 124 can be saved to additional and/or alternative data storagedevices, it should be understood that this embodiment is illustrative,and should not be construed as being limiting in any way.

From operation 408, the method 400 proceeds to operation 410. The method400 ends at operation 410.

Turning now to FIG. 5, additional details of the network 104 areillustrated, according to an illustrative embodiment. The network 104includes a cellular network 502, a packet data network 504, for example,the Internet, and a circuit switched network 506, for example, apublicly switched telephone network (“PSTN”). The cellular network 502includes various components such as, but not limited to, basetransceiver stations (“BTSs”), Node-B's or e-Node-B's, base stationcontrollers (“BSCs”), radio network controllers (“RNCs”), mobileswitching centers (“MSCs”), mobile management entities (“MMEs”), shortmessage service centers (“SMSCs”), multimedia messaging service centers(“MMSCs”), home location registers (“HLRs”), home subscriber servers(“HSSs”), visitor location registers (“VLRs”), charging platforms,billing platforms, voicemail platforms, GPRS core network components,location service nodes, an IP Multimedia Subsystem (“IMS”), and thelike. The cellular network 502 also includes radios and nodes forreceiving and transmitting voice, data, and combinations thereof to andfrom radio transceivers, networks, the packet data network 504, and thecircuit switched network 506.

A mobile communications device 508, such as, for example, a cellulartelephone, a user equipment, a mobile terminal, a PDA, a laptopcomputer, a handheld computer, and combinations thereof, can beoperatively connected to the cellular network 502. The cellular network502 can be configured as a 2G GSM network and can provide datacommunications via GPRS and/or EDGE. Additionally, or alternatively, thecellular network 502 can be configured as a 3G UMTS network and canprovide data communications via the HSPA protocol family, for example,HSDPA, EUL (also referred to as HSUPA), and HSPA+. The cellular network502 also is compatible with 4G mobile communications standards as wellas evolved and future mobile standards.

The packet data network 504 includes various devices, for example,servers, computers, databases, and other devices in communication withanother, as is generally known. The packet data network 504 devices areaccessible via one or more network links. The servers often storevarious files that are provided to a requesting device such as, forexample, a computer, a terminal, a smartphone, or the like. Typically,the requesting device includes software (a “browser”) for executing aweb page in a format readable by the browser or other software. Otherfiles and/or data may be accessible via “links” in the retrieved files,as is generally known. In some embodiments, the packet data network 504includes or is in communication with the Internet. The circuit switchednetwork 506 includes various hardware and software for providing circuitswitched communications. The circuit switched network 506 may include,or may be, what is often referred to as a plain old telephone system(POTS). The functionality of a circuit switched network 506 or othercircuit-switched network are generally known and will not be describedherein in detail.

The illustrated cellular network 502 is shown in communication with thepacket data network 504 and a circuit switched network 506, though itshould be appreciated that this is not necessarily the case. One or moreInternet-capable devices 510, for example, a PC, a laptop, a portabledevice, or another suitable device, can communicate with one or morecellular networks 502, and devices connected thereto, through the packetdata network 504. It also should be appreciated that theInternet-capable device 510 can communicate with the packet data network504 through the circuit switched network 506, the cellular network 502,and/or via other networks (not illustrated).

As illustrated, a communications device 512, for example, a telephone,facsimile machine, modem, computer, or the like, can be in communicationwith the circuit switched network 506, and therethrough to the packetdata network 504 and/or the cellular network 502. It should beappreciated that the communications device 512 can be anInternet-capable device, and can be substantially similar to theInternet-capable device 510. In the specification, the network 104 isused to refer broadly to any combination of the networks 502, 504, 506.It should be appreciated that substantially all of the functionalitydescribed with reference to the network 104 can be performed by thecellular network 502, the packet data network 504, and/or the circuitswitched network 506, alone or in combination with other networks,network elements, and the like.

FIG. 6 is a block diagram illustrating a computer system 600 configuredto provide the functionality described herein generating and usingtemporal data partition revisions, in accordance with variousembodiments of the concepts and technologies disclosed herein. Thecomputer system 600 includes a processing unit 602, a memory 604, one ormore user interface devices 606, one or more input/output (“I/O”)devices 608, and one or more network devices 610, each of which isoperatively connected to a system bus 612. The bus 612 enablesbi-directional communication between the processing unit 602, the memory604, the user interface devices 606, the I/O devices 608, and thenetwork devices 610.

The processing unit 602 may be a standard central processor thatperforms arithmetic and logical operations, a more specific purposeprogrammable logic controller (“PLC”), a programmable gate array, orother type of processor known to those skilled in the art and suitablefor controlling the operation of the server computer. Processing unitsare generally known, and therefore are not described in further detailherein.

The memory 604 communicates with the processing unit 602 via the systembus 612. In some embodiments, the memory 604 is operatively connected toa memory controller (not shown) that enables communication with theprocessing unit 602 via the system bus 612. The memory 604 includes anoperating system 614 and one or more program modules 616. The operatingsystem 614 can include, but is not limited to, members of the WINDOWS,WINDOWS CE, and/or WINDOWS MOBILE families of operating systems fromMICROSOFT CORPORATION, the LINUX family of operating systems, theSYMBIAN family of operating systems from SYMBIAN LIMITED, the BREWfamily of operating systems from QUALCOMM CORPORATION, the MAC OS, iOS,and/or LEOPARD families of operating systems from APPLE CORPORATION, theFREEBSD family of operating systems, the SOLARIS family of operatingsystems from ORACLE CORPORATION, other operating systems, and the like.

The program modules 616 may include various software and/or programmodules described herein. In some embodiments, for example, the programmodules 616 include the data management application 108. This and/orother programs can be embodied in computer-readable media containinginstructions that, when executed by the processing unit 602, perform oneor more of the methods 200-400 described in detail above with respect toFIGS. 2-4. According to embodiments, the program modules 616 may beembodied in hardware, software, firmware, or any combination thereof.Although not shown in FIG. 6, it should be understood that the memory604 also can be configured to store data from one or more of the datastreams 110, the temporal data partitions 122, the temporal metadatapartitions 124, the queries 128, the results 130, and/or other data, ifdesired.

By way of example, and not limitation, computer-readable media mayinclude any available computer storage media or communication media thatcan be accessed by the computer system 600. Communication media includescomputer-readable instructions, data structures, program modules, orother data in a modulated data signal such as a carrier wave or othertransport mechanism and includes any delivery media. The term “modulateddata signal” means a signal that has one or more of its characteristicschanged or set in a manner as to encode information in the signal. Byway of example, and not limitation, communication media includes wiredmedia such as a wired network or direct-wired connection, and wirelessmedia such as acoustic, RF, infrared and other wireless media.Combinations of the any of the above should also be included within thescope of computer-readable media.

Computer storage media includes volatile and non-volatile, removable andnon-removable media implemented in any method or technology for storageof information such as computer-readable instructions, data structures,program modules, or other data. Computer storage media includes, but isnot limited to, RAM, ROM, Erasable Programmable ROM (“EPROM”),Electrically Erasable Programmable ROM (“EEPROM”), flash memory or othersolid state memory technology, CD-ROM, digital versatile disks (“DVD”),or other optical storage, magnetic cassettes, magnetic tape, magneticdisk storage or other magnetic storage devices, or any other mediumwhich can be used to store the desired information and which can beaccessed by the computer system 600. In the claims, the phrase “computerstorage medium” and variations thereof does not include waves or signalsper se and/or communication media.

The user interface devices 606 may include one or more devices withwhich a user accesses the computer system 600. The user interfacedevices 606 may include, but are not limited to, computers, servers,personal digital assistants, cellular phones, or any suitable computingdevices. The I/O devices 608 enable a user to interface with the programmodules 616. In one embodiment, the I/O devices 608 are operativelyconnected to an I/O controller (not shown) that enables communicationwith the processing unit 602 via the system bus 612. The I/O devices 608may include one or more input devices, such as, but not limited to, akeyboard, a mouse, or an electronic stylus. Further, the I/O devices 608may include one or more output devices, such as, but not limited to, adisplay screen or a printer.

The network devices 610 enable the computer system 600 to communicatewith other networks or remote systems via a network, such as the network104. Examples of the network devices 610 include, but are not limitedto, a modem, a radio frequency (“RF”) or infrared (“IR”) transceiver, atelephonic interface, a bridge, a router, or a network card. The network104 may include a wireless network such as, but not limited to, aWireless Local Area Network (“WLAN”) such as a WI-FI network, a WirelessWide Area Network (“WWAN”), a Wireless Personal Area Network (“WPAN”)such as BLUETOOTH, a Wireless Metropolitan Area Network (“WMAN”) such aWiMAX network, or a cellular network. Alternatively, the network 104 maybe a wired network such as, but not limited to, a Wide Area Network(“WAN”) such as the Internet, a Local Area Network (“LAN”) such as theEthernet, a wired Personal Area Network (“PAN”), or a wired MetropolitanArea Network (“MAN”).

Based on the foregoing, it should be appreciated that systems andmethods for generating and using temporal metadata partitions have beendisclosed herein. Although the subject matter presented herein has beendescribed in language specific to computer structural features,methodological and transformative acts, specific computing machinery,and computer-readable media, it is to be understood that the conceptsand technologies disclosed herein are not necessarily limited to thespecific features, acts, or media described herein. Rather, the specificfeatures, acts and mediums are disclosed as example forms ofimplementing the concepts and technologies disclosed herein.

The subject matter described above is provided by way of illustrationonly and should not be construed as limiting. Various modifications andchanges may be made to the subject matter described herein withoutfollowing the example embodiments and applications illustrated anddescribed, and without departing from the true spirit and scope of theembodiments of the concepts and technologies disclosed herein.

We claim:
 1. A method comprising: obtaining metadata at a servercomputer executing a data management application, the metadatacomprising a data value and a time range associated with the data value;analyzing, by the server computer, the time range to identify a temporalmetadata partition in which the metadata is to be stored; storing, bythe server computer, the metadata in the temporal metadata partition;determining, by the server computer based upon the time range, that themetadata is to be stored in a further temporal metadata partition;storing, by the server computer, the metadata in the further temporalmetadata partition; determining that the temporal metadata partition andthe further temporal metadata partition are to be merged; and mergingthe temporal metadata partition and the further temporal metadatapartition.
 2. The method of claim 1, wherein the metadata is included ina data stream generated by a data source.
 3. The method of claim 1,wherein the metadata is included in a data stream generated by a datasource, wherein the data stream comprises the metadata and event data,and wherein the metadata defines a context of the event data.
 4. Themethod of claim 1, further comprising: receiving a query; executing thequery against event data stored in a temporal data partition to obtainan event data query result; identifying, in the event data query result,a timestamp; and retrieving the metadata from a relevant temporalmetadata partition based upon the timestamp.
 5. The method of claim 4,further comprising: computing results based upon the metadata and theevent data; and outputting the results.
 6. The method of claim 5,wherein the metadata provides a context for the event data, and whereincomputing the results comprises selecting event data based, at leastpartially, upon the metadata.
 7. The method of claim 1, whereindetermining that the temporal metadata partition and the furthertemporal metadata partition are to be merged comprises: selecting thetemporal metadata partition; and identifying the further temporalmetadata partition as a related temporal metadata partition.
 8. Themethod of claim 1, wherein merging the temporal metadata partition andthe further temporal metadata partition comprises: merging a time rangeof the temporal metadata partition with a further time range of thefurther temporal metadata partition to generate a merged temporalmetadata partition having a merged time range and the data value; andstoring the merged temporal metadata partition.
 9. A system comprising:a processor; and a memory storing computer-executable instructions that,when executed by the processor, cause the processor to performoperations comprising obtaining metadata comprising a data value and atime range associated with the data value, analyzing the time range toidentify a temporal metadata partition in which the metadata is to bestored, determining, based upon the time range, that the metadata is tobe stored in a further temporal metadata partition, storing the metadatain the further temporal metadata partition, storing the metadata in thetemporal metadata partition, determining that the temporal metadatapartition and the further temporal metadata partition are to be merged,and merging the temporal metadata partition and the further temporalmetadata partition.
 10. The system of claim 9, wherein thecomputer-executable instructions, when executed by the processor, causethe processor to perform operations further comprising: receiving aquery; executing the query against event data stored in a temporal datapartition to obtain an event data query result; identifying, in theevent data query result, a timestamp; and retrieving the metadata from arelevant temporal metadata partition based upon the timestamp.
 11. Thesystem of claim 10, wherein the computer-executable instructions, whenexecuted by the processor, cause the processor to perform operationsfurther comprising: computing results based upon the metadata and theevent data; and outputting the results.
 12. The system of claim 9,wherein the computer-executable instructions, when executed by theprocessor, cause the processor to perform operations further comprising:determining that the temporal metadata partition and the furthertemporal metadata partition are to be merged by selecting the temporalmetadata partition, and identifying the further temporal metadatapartition as a related temporal metadata partition; and merging thetemporal metadata partition and the further temporal metadata partitionby merging a time range of the temporal metadata partition with afurther time range of the further temporal metadata partition togenerate a merged temporal metadata partition having a merged time rangeand the data value, and storing the merged temporal metadata partition.13. A computer storage medium having computer-executable instructionsstored thereon that, when executed by a processor, cause the processorto perform operations comprising: obtaining metadata comprising a datavalue and a time range associated with the data value; analyzing thetime range to identify a temporal metadata partition in which themetadata is to be stored; determining, based upon the time range, thatthe metadata is to be stored in a further temporal metadata partition;storing the metadata in the further temporal metadata partition; storingthe metadata in the temporal metadata partition; determining that thetemporal metadata partition and the further temporal metadata partitionare to be merged; and merging the temporal metadata partition and thefurther temporal metadata partition.
 14. The computer storage medium ofclaim 13, further comprising computer-executable instructions that, whenexecuted by the processor, cause the processor to perform operationsfurther comprising: receiving a query; executing the query against eventdata stored in a temporal data partition to obtain an event data queryresult; identifying, in the event data query result, a timestamp; andretrieving the metadata from a relevant temporal metadata partitionbased upon the timestamp.
 15. The computer storage medium of claim 14,further comprising computer-executable instructions that, when executedby the processor, cause the processor to perform operations furthercomprising: computing results based upon the metadata and the eventdata; and outputting the results.
 16. The computer storage medium ofclaim 13, further comprising computer-executable instructions that, whenexecuted by the processor, cause the processor to perform operationsfurther comprising: determining that the temporal metadata partition andthe further temporal metadata partition are to be merged by selectingthe temporal metadata partition, and identifying the further temporalmetadata partition as a related temporal metadata partition; and mergingthe temporal metadata partition and the further temporal metadatapartition by merging a time range of the temporal metadata partitionwith a further time range of the further temporal metadata partition togenerate a merged temporal metadata partition having a merged time rangeand the data value, and storing the merged temporal metadata partition.17. The computer storage medium of claim 13, wherein the metadata isincluded in a data stream generated by a data source, wherein the datastream comprises the metadata and event data, wherein the metadatadefines a context of the event data, and wherein the temporal metadatapartition and the further temportal metadata partition are stored at adistributed database.